: Differentiation and Integration of Trisomy 21 iPSCs into Cerebral Tissues: Modeling Down Syndrome using Patient-specific iPSC-derived CNS Organoids and Humanized Chimeric Mice. Down syndrome (DS) is caused by trisomy 21, the triplication of human chromosome 21 (HSA21), and is the most common genetic cause of intellectual disability. We have successfully established and characterized multiple lines of iPSCs derived from DS patients. Particularly, we have established more than 50 DS Trisomy 21 iPSC lines, and obtained multiple pairs of corresponding isogenic disomy 21 control lines from these DS iPSCs. In addition, we have implemented CRISPR/Cas9 (Clustered Regularly Interspaced Short Palindromic Repeats/CRISPR-associated) technology in making genetic corrections in iPSCs. Modeling of human genetic diseases has previously been largely dependent upon availability of either pathological analysis of postmortem human tissue samples or recapitulation of human disease in transgenic animal models; better research tools for disease modeling are needed. Patient-specific iPSCs are excellent tools and versatile resources for this kind of translational research. As iPSCs are generated on an individual basis, iPSCs may be the optimal cellular material to use for disease modeling, drug discovery, and development of patient-specific therapies. We have already generated a significant amount of preliminary data. We have used a highly efficient CRSPR system to precisely control and normalize genes of interest on HSA21. We have also developed a system of 3- dimentional (3D) CNS organoid (CO) culture from DS iPSCs, which better recapitulates brain development and disease pathogenesis than the conventional 2-dimentional (2D) flat culture, and allows for in-depth characterization by electrophysiological assays. The CNS organoid technology represents an excellent approach for disease modeling; the cerebral organoids generated from patient iPSCs can be used as a model to recapitulate complex neural developmental diseases such as DS. In addition, we have generated a humanized chimeric mouse model, in which DS iPSC derived astrocytes are grafted to the neonatal mouse brains. The detailed genetic etiology for the various symptoms in DS remains elusive. Taking the advantage of these unique tools and resources, we will create novel in vitro and in vivo models of DS with human iPSCs derived from patients to recapitulate the defects in neural differentiation in DS. In support of the feasibility of this proposal, we have obtained the necessary materials and expertise to be used in this study, and have published a rather massive paper on DS iPSCs [Chen C, Jiang P, Xue H, Peterson SE, Tran HT, McCann AE, Parast MM, Li S, Pleasure DE, Laurent LC, Loring JF, Liu Y, Deng W. (2014) Role of astroglia in Down?s syndrome revealed by patient-derived human-induced pluripotent stem cells. Nature Communications. 5:4430 doi: 10.1038/ncomms5430 (2014)]. Our preliminary data show that both trisomy and the isogenic disomy DS astrocytes are able to repopulate the mouse brain, allowing for further interrogation of in vivo behavior of these cells and examination of their effects on neuroinflammation and cognition of the animals. Building upon prior work on multiple genes in pathways of astrocyte-mediated inflammation, we propose to produce both in vitro CNS organoids and in vivo chimeric mouse models to investigate the critical role of these astrocytic inflammatory genes (S100B, IFNAR1, IFNAR2) in development and function of DS patient-derived iPSCs. Taken together, we will use a novel platform of both an in vitro 3D organoid culture system and an in vivo humanized chimeric mouse model using DS patient-derived iPSCs. These models will provide fundamental insights into neural function in the physiological environment of 3D organoids and in early development of human cells in a living animal. The completion of the project will immensely bolster DS pathogenesis studies using patient iPSCs, as well as biochemical and molecular approaches complemented with investigation into neural network functionality. These insights will undoubtedly impact on the treatment of patients with DS.